CN110232817A - A kind of Freeway Conditions analysis method based on WiFi sniff data - Google Patents
A kind of Freeway Conditions analysis method based on WiFi sniff data Download PDFInfo
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- CN110232817A CN110232817A CN201811611749.4A CN201811611749A CN110232817A CN 110232817 A CN110232817 A CN 110232817A CN 201811611749 A CN201811611749 A CN 201811611749A CN 110232817 A CN110232817 A CN 110232817A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/012—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from other sources than vehicle or roadside beacons, e.g. mobile networks
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0133—Traffic data processing for classifying traffic situation
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Traffic Control Systems (AREA)
Abstract
The present invention provides a kind of Freeway Conditions analysis method based on WiFi sniff data, it is related to intelligent transportation real-time road analysis field, the method includes the steps 1: in highway scene, every 3km forms a section and lays WiFi sniff equipment, obtains the mac address information of passenger's smart phone；Step 2: by continuous 2 section range differences and the time difference for collecting the same mac address information, calculating the average overall travel speed that passenger passes through 2 sections；Step 3: the section real time running speed is calculated by the average overall travel speed of the multiple mac address informations of continuous 2 sections.The WiFi sniff equipment that the present invention passes through the certain power of laying, every 3km or so forms a detection section, all standing is carried out to highway detection section, the demand that real-time road is analyzed under highway scene is realized, freeway management department is helped to realize real-time security management.
Description
Technical field
The present invention relates to intelligent transportation real-time road analysis field more particularly to a kind of high speeds based on WiFi sniff data
Highway condition analysis method.
Background technique
Currently, smart phone becomes indispensable in people's lives with the development of mechanics of communication and electronic technology,
And it is on very close terms.On the one hand, the function of smart phone is stronger and stronger, and frequency of use is higher and higher, and government provides much just
The service of benefit, such as WiFi under various scenes exempt from traffic service, so many mobile phone users often beat WiFi function
It opens, therefore provides excellent basis for the application of WiFi detection of passenger flow technology.
On the other hand, with the raising of monitoring technology, WiFi sniff equipment be may be implemented to smart phone in controlled range
Detectability, by adjusting the power of WiFi sniff equipment, the range of adjustable monitoring adjusts the range of detection, detection
Radius can achieve 150 meters or even farther, such as by taking 150 meters of radiuses as an example, and diameter is close to 300 meters, even if in 150Km/h speed
Degree downward driving passes through central area, it is also desirable to 7 seconds.However WiFi sniff equipment scanning speed is 200 milliseconds or so, has height
To the detectability of mobile device under fast highway scene.
For the real-time road analytical technology under highway scene, similar product is based primarily upon video detecting method and base
It is realized in mobile phone signaling test method.Wherein, based on the passenger flow detection method of video, by identification vehicle license plate come analysis meter
Real-time road is calculated, this method precision is higher, but construction and maintenance cost are high, need often to conserve camera lens, will receive light
According to, the factor of rainwater, dust, and influence detection.Based on the detection method of mobile phone signaling, it is confined to the distribution of base station, even if
Downtown, detection radius is also in several hundred rice under highway scene, base station distribution is rare, and detection accuracy is low, timeliness
Difference.
And the detection of passenger flow technology based on WiFi sniff, (the detection of different plant capacities can be selected according to scene demand
Distance is from tens meters~several hundred meters radiuses), and different implantation of device density can be designed.Therefore, this method is suitable for high speed
Road condition analyzing demand under highway scene.
Summary of the invention
In view of the foregoing deficiencies of prior art, the purpose of the present invention is to provide a kind of based on WiFi sniff data
Freeway Conditions analysis method, by laying the WiFi sniff equipment of certain power, it is disconnected that every 3km or so forms a detection
Face carries out all standing to highway detection section, realizes the demand that real-time road is analyzed under highway scene, help high
Fast highway administration department realizes real-time security management.
The present invention provides a kind of Freeway Conditions analysis method based on WiFi sniff data, and the method includes following
Step:
Step 1: in highway scene, every 3km forms a section and lays WiFi sniff equipment, obtains passenger's intelligence hand
The mac address information of machine；
Step 2: by continuous 2 section range differences and the time difference for collecting the same mac address information, calculating passenger
Pass through the average overall travel speed of 2 sections；
Step 3: the section real time running is calculated by the average overall travel speed of the multiple mac address informations of continuous 2 sections
Speed.
Further, the passenger calculates that steps are as follows by the average overall travel speed of two sections:
Step 2.1: the mac address information that WiFi sniff equipment detects is uploaded onto the server in real time；
Step 2.2: server is detected same by continuous 2 section range differences and continuous two WiFi sniff equipment
The time difference of mac address information calculates the average overall travel speed that passenger passes through 2 sections.
Further, the real time running speed calculation step is as follows:
Step 3.1: by continuous 2 sections, in different driving directions beginning and end each other, in a measurement period,
Detect the average overall travel speed that multiple single mac address informations correspond to passenger；
Step 3.2: by clustering, taking the root mean sequare velocity of 90% confidence interval sample as the real-time row in the section
Sail speed.
As described above, a kind of Freeway Conditions analysis method based on WiFi sniff data of the invention, has following
The utility model has the advantages that WiFi sniff equipment of the present invention by the certain power of laying, every 3km or so forms a detection section, to height
Fast highway detection section carries out all standing, realizes the demand that real-time road is analyzed under highway scene, helps highway
Administrative department realizes real-time security management, and the accuracy rate of highway scene real-time road is high, can be used as highway reality
Effective reference of Shi Lukuang.
Detailed description of the invention
Fig. 1 is shown as highway real-time road analysis method block diagram disclosed in the embodiment of the present invention；
Fig. 2 is shown as schematic diagram of the highway disclosed in the embodiment of the present invention from a section to next section；
Specific embodiment
Illustrate embodiments of the present invention below by way of specific specific example, those skilled in the art can be by this specification
Other advantages and efficacy of the present invention can be easily understood for disclosed content.The present invention can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also based on different viewpoints and application, without departing from
Various modifications or alterations are carried out under spirit of the invention.It should be noted that in the absence of conflict, following embodiment and implementation
Feature in example can be combined with each other.
It should be noted that illustrating the basic structure that only the invention is illustrated in a schematic way provided in following embodiment
Think, only shown in diagram then with related component in the present invention rather than component count, shape and size when according to actual implementation
Draw, when actual implementation kenel, quantity and the ratio of each component can arbitrarily change for one kind, and its assembly layout kenel
It is likely more complexity.
As shown in Figure 1, the present invention provides a kind of Freeway Conditions analysis method based on WiFi sniff data, the side
Method the following steps are included:
Step 1: in highway scene, every 3km forms a section and lays WiFi sniff equipment, obtains passenger's intelligence hand
The mac address information of machine；
Step 2: by continuous 2 section range differences and the time difference for collecting the same mac address information, calculating passenger
Pass through the average overall travel speed of 2 sections；
As shown in Fig. 2, WiFi sniff equipment be it is multiple, to highway detection section carry out all standing.Wherein, WiFi is smelt
Spy technology is based on IEEE 802.11 (IEEE: Institute of Electrical and Electric Engineers) agreement and defines AP in standard agreement
Two kinds of operating modes of (WiFi sniff equipment) and STA (stand or client)；BEACON (beacon frame), ACK are defined in agreement
A variety of wireless data frame types such as (acknowledgement frame), DATA (data frame), PROBE (detection frame).Sniff equipment can be periodically to four
Week broadcast BEACON can initiate the connection inquiry after smart phone receives；Smart phone can constantly send BEACON, be detected
Inquire which AP is can to access.According to the frame format of 802.11 agreement of IEEE, BEACON (beacon frame), ACK (acknowledgement frame),
It include the mac address information of website, MAC Address letter in the wireless data frames such as DATA (data frame), PROBE (detection frame)
Breath is in MAC header (MAC header) field of wireless data frame.
The WiFi sniff equipment for being set to section of expressway receives the PROBE (detection frame) that the smart phone of passenger is sent
Etc. wireless data frames, the MAC Address of smart phone, the movement velocity of smart phone can be parsed from these wireless data frames
And the movement velocity for vehicle where mobile phone holder.Because occupation rate of the smart phone in highway passenger is very high,
Therefore, it will detect that a large amount of mac address information in the express highway section with certain vehicle flowrate.
Because of the mac address information of the same smart phone, may be detected by continuous multiple WiFi sniff equipment, because
This, the mac address information that WiFi sniff equipment detects is uploaded onto the server in real time, and server passes through continuous 2 section distances
The time difference of the poor and collected same mac address information can calculate the average overall travel speed V that passenger passes through 2 sections
=dis/ (t2-t1), wherein dis is the distance between two sections, and t2 and t1 are distributed as the WiFi sniff of two section parts setting
Equipment detects the time of the same mac address information.
Wherein, WiFi sniff equipment can find the mac address information of periphery smart phone, but not go to connect, therefore not
It will affect communication.
Step 3: the section real time running is calculated by the average overall travel speed of the multiple mac address informations of continuous 2 sections
Speed.
Continuous 2 sections, in different driving directions beginning and end each other.For taking a direction, counted at one
In period, it will the average overall travel speed for detecting multiple MAC takes the square of 90% confidence interval sample by clustering
Root speed as continuous 2 sections the direction actual travel speed (road conditions).
In conclusion WiFi sniff equipment of the present invention by the certain power of laying, it is disconnected that every 3km or so forms a detection
Face carries out all standing to highway detection section, realizes the demand that real-time road is analyzed under highway scene, help high
Fast highway administration department realizes real-time security management, and the accuracy rate of highway scene real-time road is high, can be used as high speed
Effective reference of highway real-time road.So the present invention effectively overcomes various shortcoming in the prior art and has high industrial
Utility value.
The above-described embodiments merely illustrate the principles and effects of the present invention, and is not intended to limit the present invention.It is any ripe
The personage for knowing this technology all without departing from the spirit and scope of the present invention, carries out modifications and changes to above-described embodiment.Cause
This, institute is complete without departing from the spirit and technical ideas disclosed in the present invention by those of ordinary skill in the art such as
At all equivalent modifications or change, should be covered by the claims of the present invention.
Claims (3)
1. a kind of Freeway Conditions analysis method based on WiFi sniff data, which is characterized in that the method includes following
Step:
Step 1: in highway scene, every 3km forms a section and lays WiFi sniff equipment, obtains passenger's smart phone
Mac address information；
Step 2: by continuous 2 section range differences and the time difference for collecting the same mac address information, calculating passenger and pass through
The average overall travel speed of 2 sections；
Step 3: the section real time running speed is calculated by the average overall travel speed of the multiple mac address informations of continuous 2 sections.
2. the Freeway Conditions analysis method according to claim 1 based on WiFi sniff data, it is characterised in that: institute
It states passenger and calculates that steps are as follows by the average overall travel speed of two sections:
Step 2.1: the mac address information that WiFi sniff equipment detects is uploaded onto the server in real time；
Step 2.2: server detects the same MAC by continuous 2 section range differences and continuous two WiFi sniff equipment
The time difference of address information calculates the average overall travel speed that passenger passes through 2 sections.
3. the Freeway Conditions analysis method according to claim 1 based on WiFi sniff data, it is characterised in that: institute
It is as follows to state real time running speed calculation step:
Step 3.1: by continuous 2 sections, in different driving directions, beginning and end detects in a measurement period each other
Multiple list mac address informations correspond to the average overall travel speed of passenger；
Step 3.2: by clustering, taking real time running speed of the root mean sequare velocity of 90% confidence interval sample as the section
Degree.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811611749.4A CN110232817A (en) | 2018-12-27 | 2018-12-27 | A kind of Freeway Conditions analysis method based on WiFi sniff data |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201811611749.4A CN110232817A (en) | 2018-12-27 | 2018-12-27 | A kind of Freeway Conditions analysis method based on WiFi sniff data |
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| CN110232817A true CN110232817A (en) | 2019-09-13 |
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| CN201811611749.4A Withdrawn CN110232817A (en) | 2018-12-27 | 2018-12-27 | A kind of Freeway Conditions analysis method based on WiFi sniff data |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110913345A (en) * | 2019-11-15 | 2020-03-24 | 东南大学 | Section passenger flow calculation method based on mobile phone signaling data |
| CN111260805A (en) * | 2020-01-15 | 2020-06-09 | 南京信息工程大学 | High-speed unmanned charging method based on WiFi sniffing technology |
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| CN102062866A (en) * | 2010-10-14 | 2011-05-18 | 北京交通发展研究中心 | Method and device for calculating travelling speed between two geographic positions |
| CN104778840A (en) * | 2015-04-30 | 2015-07-15 | 南京中大东博信息科技有限公司 | Vehicle information sensing system and method |
| CN106097731A (en) * | 2016-08-16 | 2016-11-09 | 寿光明 | Traffic flow detector based on WIFI signal and detecting system |
| CN106251646A (en) * | 2016-08-16 | 2016-12-21 | 寿光明 | Traffic flow detection system based on WIFI signal and detection method |
| CN108198435A (en) * | 2017-08-22 | 2018-06-22 | 中兴通讯股份有限公司 | A kind of measuring method and device |
| CN108242147A (en) * | 2016-12-27 | 2018-07-03 | 杭州海康威视系统技术有限公司 | Traffic method of estimation, apparatus and system |
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2018
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Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102062866A (en) * | 2010-10-14 | 2011-05-18 | 北京交通发展研究中心 | Method and device for calculating travelling speed between two geographic positions |
| CN104778840A (en) * | 2015-04-30 | 2015-07-15 | 南京中大东博信息科技有限公司 | Vehicle information sensing system and method |
| CN106097731A (en) * | 2016-08-16 | 2016-11-09 | 寿光明 | Traffic flow detector based on WIFI signal and detecting system |
| CN106251646A (en) * | 2016-08-16 | 2016-12-21 | 寿光明 | Traffic flow detection system based on WIFI signal and detection method |
| CN108242147A (en) * | 2016-12-27 | 2018-07-03 | 杭州海康威视系统技术有限公司 | Traffic method of estimation, apparatus and system |
| CN108198435A (en) * | 2017-08-22 | 2018-06-22 | 中兴通讯股份有限公司 | A kind of measuring method and device |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110913345A (en) * | 2019-11-15 | 2020-03-24 | 东南大学 | Section passenger flow calculation method based on mobile phone signaling data |
| CN111260805A (en) * | 2020-01-15 | 2020-06-09 | 南京信息工程大学 | High-speed unmanned charging method based on WiFi sniffing technology |
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Application publication date: 20190913 |